Multi-detector row computed tomography (MDCT) allows the acquisition of high-resolution data of the entire thorax. The quality of the data allows the assessment of the bronchi as well as the pulmonary artery tree. Extraction of the pulmonary artery tree is an important pre-processing step, e.g., for embolism detection. Also, in the quantitative assessment of the bronchial tree the accompanying artery tree contains important additional information that can be extracted from MDCT data. Hence, for diagnosis and treatment of asthmatic and emphysematic patients, the simultaneous assessment of the tracheobronchial tree and the accompanying pulmonary artery tree is crucial. E.g., the ratio of inner bronchial to accompanying arterial diameter is an important parameter in clinical practice in order to detect and quantify airway narrowing and bronchial dilation.
When extracting the pulmonary vessel tree from Multi-Slice CT data, difficulties arise when distinguishing pulmonary arteries from veins. For instance, seed-point based region expansion methods for the extraction of the pulmonary arteries suffer from leakage into pulmonary veins Hitherto known methods extract all vessels, i.e. the pulmonary arteries and veins, without making any distinction. Furthermore, the segmentations of the tracheobronchial tree and the pulmonary vessel tree are performed separately and thus the relation between the trees is not inherent in the segmentation result. Hence, these methods are not well suited for clinical practice.
De Jong P A et al. (Pulmonary disease assessment in cystic fibrosis: comparison of CT scoring systems and value of bronchial and arterial dimension measurements, Radiology, vol. 231, no. 2, pp. 434-439, May 2004) disclose a method of radius measurements of bronchi and accompanying arteries and the identification of bronchus/artery pairs. However, the disclosed method is performed manually by human observers. Hence, this method is based on a mental act of the individual observer an consequently it is prone to errors. For instance the quality of the identification depends on the experience of the individual performing the extraction, his/her concentration capability at the time of evaluation, etc.
Hence, an object of the present invention is to provide an advantageous automatically performed artery/vein separation in medical 3D images.